Vodafone Idea - Senior Data Scientist - Advanced Analytics & AI

: Senior Data Scientist (Telecom Domain)
Location: Mumbai, India
Department: Advanced Analytics & AI
Position Overview:
We are seeking a highly skilled Senior Data Scientist to design, build, and scale our next-generation AI/ML platforms. In this role, you will leverage telecom data to architect production-ready personalization and recommendation engines. You will lead the integration of Generative AI and Agentic frameworks within our secure AWS cloud ecosystem.
Key Responsibilities:
1. AI/ML Development & Personalization:
- Design and deploy high-performance recommendation systems to drive customer retention, ARPU (Average Revenue Per User), and cross-selling.
- Build advanced machine learning (ML), deep learning (DL), and natural language processing (NLP) models to parse complex network and customer interactions.
- Architect and implement cutting-edge Generative AI solutions and autonomous Agentic AI frameworks to automate complex customer and operational workflows.

2. Data Engineering & Production Pipelines:
- Construct, optimise, and maintain robust data pipelines and production-grade ML pipelines (MLOps) for real-time and batch processing.
- Work closely with data engineers to transform massive, unstructured telecom datasets into clean feature stores.
3. Cloud Architecture & Systems Design:
- Own the end-to-end ML lifecycle on AWS Cloud, utilizing services like SageMaker, EMR, Glue, Lambda, and Bedrock.
- Design scalable, fault-tolerant AI architectures that cleanly integrate with core telecom network systems.
4. Analytics & Visualisation:
- Perform deep-dive exploratory data analysis to uncover commercial and operational trends.
- Present complex model metrics and business KPIs to executive leadership using interactive dashboards and reporting tools.
Required Technical Skills:
1. Core Programming:
- Elite Python skills with absolute mastery of data science libraries (NumPy, Pandas, Scikit-Learn, PyTorch, or TensorFlow).
2. Big Data & Querying:
- Advanced proficiency in PySpark for distributed computing, alongside expert-level SQL skills for handling relational and non-relational databases.
3. Generative & Agentic AI:
- Hands-on experience building multi-agent systems using frameworks like LangChain, CrewAI, AutoGen, or LlamaIndex.
4. Cloud Infrastructure:
- Strong working knowledge of AWS environments, IAM policies, and cloud data warehousing.
5. Data Visualisation:
- Proficiency in building clean visual stories using tools like Tableau, Power BI, QuickSight, or advanced Excel.
Qualifications & Experience:
- Experience: Minimum 5 years of professional data science experience, with a proven track record of shipping ML products to production.
- Domain: Previous experience in the Telecom sector handling Call Detail Records (CDR), subscriber behaviour, or churn modeling is highly preferred.
- Education: Bachelors or Masters degree.